Aggregation of Probabilistic Opinions

概率意见的汇总

• 批准号: 0241434
• 负责人: David Budescu
• 金额: $ 22.5万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-03-15 至 2007-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0241434&HistoricalAwards=false
• 关键词: Aggregation; Probabilistic; Opinions

This proposal focuses on the aggregation process used by individual Decision-Makers (DMs) to combine probabilistic information from multiple, non-independent sources. Typical examples are investors who combine forecasts from various financial advisors regarding the chances of certain stocks to appreciate in value, and patients who must aggregate information from various experts about the chances of success of a given medical procedure.A model is described that assumes that (a) the DM combines information by averaging the various forecasts, and (b) the DM's confidence in the aggregate is inversely related to the variance of the (possibly weighted) mean forecast. This model is used to derive a series of predictions about the factors that affect and drive the DM's confidence. They will be tested in a series of experiments that would clarify (a) the nature of the aggregation rules used by DMs, (b) the factors that affect the DMs' confidence in the final aggregate, (c) the nature and level of dependence between the aggregates and the confidence they inspire, and (d) the factors that determine the DM's preference for certain advisors.In addition to contributing to our understanding of the basic psychological process involved in aggregating opinions, the results have immediate implications for several questions of considerable practical interest that arise in many fields including, but not restricted to, financial, military and medical decision-making. The results will provide (at least partial) guidelines for approaching questions such as:(a) What kind of, and how many, advisors should a DM consult to achieve a desired level of confidence?(b) What factors make some advisors more or less attractive in certain types of decision problems?(c) What are the sources of the surprisingly high correlation among advisors? What is the relative importance of the various factors and how can one use this information to choose advisors in an optimal fashion?

该提案着重于个人决策者（DMS）使用的聚合过程，以结合来自多个非独立来源的概率信息。 典型的例子是将各种财务顾问的预测结合在一起的投资者，这些顾问就某些股票的价值欣赏的机会，以及必须从各种专家那里汇总有关给定医疗程序成功机会的患者。 a）DM通过平均各种预测来结合信息，并且（b）DM对骨料的信心与（可能加权）平均预测的方差成反比。 该模型用于得出有关影响和推动DM信心的因素的一系列预测。 它们将在一系列实验中进行测试，以阐明（a）DMS使用的聚合规则的性质，（b）影响DMS对最终骨料信心的因素，（c）依赖性的性质和水平在聚集体和他们启发的信心之间以及（d）决定DM偏爱某些顾问的因素。除了为我们对汇总意见涉及的基本心理过程的理解做出贡献外，结果对几个问题具有直接的意义在许多领域，包括但不限于金融，军事和医疗决策，都产生了相当大的实际利益。 结果将为诸如：（a）诸如以下问题的问题提供（至少部分）指南在某些类型的决策问题中吸引力较小？（c）顾问之间令人惊讶的高度相关性的来源是什么？各种因素的相对重要性是什么？如何使用此信息以最佳方式选择顾问？